Yi-Ming (Amy) Chang

603-***-**** ac8lb1@r.postjobfree.com linkedin.com/in/yimingchang

QUALIFICATION

§ Solid understanding the knowledge of data cleansing, data manipulation, data analysis, and data visualization

§ Experience with SQL and Excel – ability to manipulate complex, highly-optimized queries across large volumes of data

§ Capability with data analysis method and predictive modeling using Python and R to solve complex problems

§ Ability with data visualization tools: Tableau and Power BI to create impact reports and interactive dashboard to gain insights

§ Be able to multi-task and manage variety of programs in response to business priority

§ Excellent analytical, organizational, and written/verbal communication skills

§ Strong time management skill

EDUCATION

§ Master of Science in Analytics & Data Science May 2018 – May 2019 University of New Hampshire, USA

Current accumulated GPA: 3.75

Relevant courses: Intro: Applied Analytic Stats, Foundations of Data Analytics, Tools and Foundations, Intro Analytics Applications, Topics/Data Visualization, Data Architecture, Analytics Applications I, Analytics Practicum I, Analytics Method, Analytics Applications II, Analytics Practicum II

§ Bachelor of Business Administration in Finance Sep. 2007 – June 2011 Tunghai University, Taiwan

SKILL SUMMARY

Data Driven Analysis Project Management International Business & Logistics

- Technical Skills and System Experience: Tableau Desktop, Tableau Prep, Power BI, JMP, MS Project, Word, Excel, PowerPoint, Data Analysis, Data Visualization, Predictive Modeling, Product Development, Project Management, Lifecycle Management, Interpersonal Problem-Solving in Banking Field, Consultative Sales

- Programming Language: Python, R, SQL, SAS

EXPERIENCE

§ University of New Hampshire

Successfully complete multiple projects related to analytics and data science May 2018 – Dec. 2018

• Health Club Simulation project

- Simulate the balance between customers’ user experience and the maximum tolerance of time limitation

- Analyze the optimal maximum usage time for each member during peak hours

• Higher Education System Evaluation

- Conduct hypothesis test to evaluate how an educational degree is valued with large number of features

• Washington, D.C.'s Bike-Sharing Insights

- Data cleansing and pivot table by using two sources of the datasets

- Predict bike usage based on various features

(a) Evaluate with Regression model: Multiple Linear Regression & K-Nearest Neighbor

(b) Analyze with Classification model: Logistic Regression & Naïve Bayes’

• Box Office Predictor

- Conduct Python web scraping and Naïve Bayes’ Theorem to build box office predictor

(a) Web scraping IMDb and MOJO Box Office

(b) Predict whether specific combination will hit the desired target gross

• Airline On-Time Performance Simulation project

- Data cleansing and feature creation to analyze airline on time performance

• High dimensional reduction practice

- Use Python to conduct t-Distributed Stochastic Neighbor Embedding (tSNE), Multidimensional scaling (MDS), and Partial least squares regression (PLS)

• Baby Names Insights: Friends Trend

- Use SQL, Tableau, and Power BI to estimate the relationship between the popularity of the TV series and how parents name their children

• Analyze Minneapolis, Minnesota Crime Insights

• Google Store Insights

- Use ShinyAPP and handle commits on GitHub/BitBucket

- Data preparation from data cleaning, pivot table to data analysis, and data visualization with story and dashboard

• Twitter information analysis and visualization

- Use R to collect data from Twitter for analysis (#Florence) and create visualization chart

• New Hampshire Traffic Insights (Group Project)

- Use R to discover insights regarding to the drivers who have been stopped or pulled over in New Hampshire

• Evaluate the US Healthcare System (Group Project)

- Explore “Next Disease, Current Provider Trend, and Inefficiencies” from three different aspects, including Disease Burden, Access and Inequality, and Healthcare Delivery

• Lending Club Assessment (Group Project)

- Look into imbalanced classes, outliers, multicollinearity, and scaling and standardization

- Use various modeling techniques like shrinkage methods (Lasso, Ridge, Elastic Net), partition methods (random forest, gradient boosting) and comparing these methods with the conventional logistic regression model

- Compare profiles of each grade between pre and post IPO periods

• Commander-in-Tweet (Group Project)

- Data collection, data cleansing, data analysis/interpretation, and data visualization to analyze the sentiments and emotions of Donald J. Trump and the People of Twitter

§ ASUS TECHNOLOGY COMPUTER INCORPORATION

Project Manager Feb. 2014 – Mar. 2017

• Handled projects

- Scheduled developing criteria and milestone

- Initiated and oversaw certification plans, such as BQB, Wi-Fi CERTIFIEDTM, and Google approval

- Coordinated and boosted cross-department cooperation

• Managed the quality of production image, including Pre-burn Image and Factory Image

- Integrated R&D to develop demanded factory image and test tools. Monitored the efficiency and accuracy for both.

- Collected issues occurring in the factory and coordinated to eliminate

• Monitored the quality of Shipping Image on JIRA

• Conducted, motivated, and implemented demo plan for Computex 2016

• Built troubleshooting training course for Customer Service Center and created Standard Operating Procedures Sales Administrator Feb. 2012 – Jan. 2014

• Order management

- Handled customer Purchase Orders and media sample orders in Oracle system

- Tracked fulfillment status with OEM factories to achieve customer and sales demand

- Arranged shipping and delivery, supported import and export process and handled customer clearance issues

- Enhanced the function of sales report by combining and cleaning from different data sources

• Account receivable management

- Generated and released invoices for sale transactions

- Tracked customers debt and accounts overdue, write off received payment from the account

• Supported Insurance Claim

• Communicated with customers or sales to resolve issues

§ Bank SinoPac Ltd.

Personal Banker Sep. 2011 – Jan. 2012

• Customer service: built and maintained the relationship with clients

• Developed the market of customer’s mortgage requirement Auditor July 2011 – Sep. 2011

• Data mining, and customer profiling and segmentation

• Identification verification

• Credit check and rating

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